Si loin, si proches ? La comparaison France / Québec en sciences sociales So near, so far? The France / Quebec comparison in social sciences
Bibliographic record
Abstract
Les travaux comparatifs qui s’appuient sur au moins un cas québécois et un cas français se sont multipliés ces dix dernières années. En décidant la question de la comparaison à travers le doublet France / Québec, le colloque s’intéresse aux origines et aux effets propres de ce vis-à-vis comparatif, mais aussi aux relations entre espaces politiques et intellectuels que cette comparaison privilégiée illustre et alimente. Ainsi, en examinant les méthodes et les catégories de ces entreprises comparatives, en discutant – en-deçà et au-delà des cadres nationaux – des échelles de la comparaison et en analysant les circulations transatlantiques, ces deux journées permettront, pour la première fois, d’évaluer l’ampleur et les formes privilégiées de la comparaison entre ces deux contextes, « si loin, si proches ».
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".